#ifndef CAFFE_EMBED_LAYER_HPP_
#define CAFFE_EMBED_LAYER_HPP_

#include <vector>
#include "caffe/blob.hpp"
#include "caffe/layer.hpp"
#include "caffe/proto/caffe.pb.h"


namespace caffe {

/* @brief A layer for learning "embeddings" of one-hot vector input.
 *        Equivalent to an InnerProductLayer with one-hot vectors as input, 
 *        but for efficiency the input is the "hot" index of each column itself.
 * TODO(dox): thorough documentation for Forward, Backward, and proto params. */
template <typename Dtype>
class EmbedLayer : public Layer<Dtype> {
 public:
  explicit EmbedLayer(const LayerParameter& param) : Layer<Dtype>(param) {}
  virtual void LayerSetUp(const vector<Blob<Dtype>*>& bottom, const vector<Blob<Dtype>*>& top);
  virtual void Reshape(const vector<Blob<Dtype>*>& bottom, const vector<Blob<Dtype>*>& top);

  virtual inline const char* type() const { return "Embed"; }
  virtual inline int ExactNumBottomBlobs() const { return 1; }
  virtual inline int ExactNumTopBlobs() const { return 1; }

 protected:
  virtual void Forward_cpu(const vector<Blob<Dtype>*>& bottom, const vector<Blob<Dtype>*>& top);
  virtual void Backward_cpu(const vector<Blob<Dtype>*>& top, const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom);

  int M_;
  int K_;
  int N_;
  bool bias_term_;
  Blob<Dtype> bias_multiplier_;
};

}  // namespace caffe
#endif  // CAFFE_EMBED_LAYER_HPP_
